rare for a stocks highest trade price to never reach it's close on the previous day, especially during a generally bullish market.

The stark contrast between the 10-20% bucket vs. the others is very surprising. All other categories have a negatively-sloped line but 10-20% has a significant positive slope. If we carried this out further than 5 days we can assume it would achieve a similar slope to the other categories.

Why the swift partial recovery for 10-20%? One point to note is that of all the stocks found in this category their average drop on that initial day was about 12%. We then see them reach an average daily price high of about 9.5%

The way stocks react to significant price shocks is important for finding good entry and exit points. A common question traders and investors ask themselves is whether to purchase after a stock takes a big fall on a bad earnings report, for example.

If we're to believe the efficient market hypothesis then the shocked stocks price is reflective of all new information so wouldn't warrant a purchase (based solely on the price shock.) However, if there are exceptions to the EMH, or if it takes time for the price to reach it's EMH point, then there is value in studying reactions to price shocks.

In this article we'll study how stocks recover from various levels of price drops in one day. This will help us understand if there is any advantage to purchasing directly after one of these events.

Analysis Setup

The data was based off a group of randomly selected days from the years 2004, 2005 and 2006. The next few days afterwards were then analyzed to build the statistics below.

Stock price was restricted to those above $1. This was done because penny stocks are very volatile and could skew the data. Studying penny stocks is very interesting as well, but a separate concern.

Stock volume was restricted to those above 25,000 on a daily basis. Again, this was done to prevent skews in the data. Low-volume stocks behave differently than larger volume ones.

Buckets were created for easier representation and analysis, based on the amount of the initial price shock. The buckets were chosen as 1-5% drop, 5-10%, 10-20%, and an extra one for all stocks as a comparison.

Note: The selection of the years 2004, 2005 and 2006 as the period for the test has implications we should expect up-front. The market during this period was generally considered bullish we should expect somewhat different results were we to analyze a bearish period.

Tracking price high after the drop

The first part of the analysis was to examine the price highs achieved several days after a significant downward price shock. We'll check the performance of the stocks in each bucket for several days after the drop.

Here are the average price highs achieved by each bucket 1, 2, 3, 4 and 5 days after the initial drop compared to the close on the drop day:

• All stocks: 2%, 1.5%, 1.0%, 1.4%, 1.5%
• 1-5% drop: 2.1%, 1.9%, 1.5%, 1.6%, 1.8%
• 5-10% drop: 3.8%, 3.2%, 2.3%, 2.4%, 2.5%
• 10-20% drop: 4.2%, 3.5%, 7.1%, 6.8%, 9.4%

Analysis

First of all, there are no negative values because we're looking at the highs. It would be very rare for a stocks highest trade price to never reach it's close on the previous day, especially during a generally bullish market.

The stark contrast between the 10-20% bucket vs. the others is very surprising. All other categories have a negatively-sloped line but 10-20% has a significant positive slope. If we carried this out further than 5 days we can assume it would achieve a similar slope to the other categories.

Why the swift partial recovery for 10-20%? One point to note is that of all the stocks found in this category their average drop on that initial day was about 12%. We then see them reach an average daily price high of about 9.5% h

rious levels of price drops in one day. This will help us understand if there is any advantage to purchasing directly after one of these events.

Analysis Setup

The data was based off a group of randomly selected days from the years 2004, 2005 and 2006. The next few days afterwards were then analyzed to build the statistics below.

Stock price was restricted to those above $1. This was done because penny stocks are very volatile and could skew the data. Studying penny stocks is very interesting as well, but a separate concern.

Stock volume was restricted to those above 25,000 on a daily basis. Again, this was done to prevent skews in the data. Low-volume stocks behave differently than larger volume ones.

Buckets were created for easier representation and analysis, based on the amount of the initial price shock. The buckets were chosen as 1-5% drop, 5-10%, 10-20%, and an extra one for all stocks as a comparison.

Note: The selection of the years 2004, 2005 and 2006 as the period for the test has implications we should expect up-front. The market during this period was generally considered bullish we should expect somewhat different results were we to analyze a bearish period.

Tracking price high after the drop

The first part of the analysis was to examine the price highs achieved several days after a significant downward price shock. We'll check the performance of the stocks in each bucket for several days after the drop.

Here are the average price highs achieved by each bucket 1, 2, 3, 4 and 5 days after the initial drop compared to the close on the drop day:

• All stocks: 2%, 1.5%, 1.0%, 1.4%, 1.5%
• 1-5% drop: 2.1%, 1.9%, 1.5%, 1.6%, 1.8%
• 5-10% drop: 3.8%, 3.2%, 2.3%, 2.4%, 2.5%
• 10-20% drop: 4.2%, 3.5%, 7.1%, 6.8%, 9.4%

Analysis

First of all, there are no negative values because we're looking at the highs. It would be very rare for a stocks highest trade price to never reach it's close on the previous day, especially during a generally bullish market.

The stark contrast between the 10-20% bucket vs. the others is very surprising. All other categories have a negatively-sloped line but 10-20% has a significant positive slope. If we carried this out further than 5 days we can assume it would achieve a similar slope to the other categories.

Why the swift partial recovery for 10-20%? One point to note is that of all the stocks found in this category their average drop on that initial day was about 12%. We then see them reach an average daily price high of about 9.5%

ews in the data. Low-volume stocks behave differently than larger volume ones.

Buckets were created for easier representation and analysis, based on the amount of the initial price shock. The buckets were chosen as 1-5% drop, 5-10%, 10-20%, and an extra one for all stocks as a comparison.

Note: The selection of the years 2004, 2005 and 2006 as the period for the test has implications we should expect up-front. The market during this period was generally considered bullish we should expect somewhat different results were we to analyze a bearish period.

Tracking price high after the drop

The first part of the analysis was to examine the price highs achieved several days after a significant downward price shock. We'll check the performance of the stocks in each bucket for several days after the drop.

Here are the average price highs achieved by each bucket 1, 2, 3, 4 and 5 days after the initial drop compared to the close on the drop day:

• All stocks: 2%, 1.5%, 1.0%, 1.4%, 1.5%
• 1-5% drop: 2.1%, 1.9%, 1.5%, 1.6%, 1.8%
• 5-10% drop: 3.8%, 3.2%, 2.3%, 2.4%, 2.5%
• 10-20% drop: 4.2%, 3.5%, 7.1%, 6.8%, 9.4%

Analysis

First of all, there are no negative values because we're looking at the highs. It would be very rare for a stocks highest trade price to never reach it's close on the previous day, especially during a generally bullish market.

The stark contrast between the 10-20% bucket vs. the others is very surprising. All other categories have a negatively-sloped line but 10-20% has a significant positive slope. If we carried this out further than 5 days we can assume it would achieve a similar slope to the other categories.

Why the swift partial recovery for 10-20%? One point to note is that of all the stocks found in this category their average drop on that initial day was about 12%. We then see them reach an average daily price high of about 9.5%

amine the price highs achieved several days after a significant downward price shock. We'll check the performance of the stocks in each bucket for several days after the drop.

Here are the average price highs achieved by each bucket 1, 2, 3, 4 and 5 days after the initial drop compared to the close on the drop day:

• All stocks: 2%, 1.5%, 1.0%, 1.4%, 1.5%
• 1-5% drop: 2.1%, 1.9%, 1.5%, 1.6%, 1.8%
• 5-10% drop: 3.8%, 3.2%, 2.3%, 2.4%, 2.5%
• 10-20% drop: 4.2%, 3.5%, 7.1%, 6.8%, 9.4%

Analysis

First of all, there are no negative values because we're looking at the highs. It would be very rare for a stocks highest trade price to never reach it's close on the previous day, especially during a generally bullish market.

The stark contrast between the 10-20% bucket vs. the others is very surprising. All other categories have a negatively-sloped line but 10-20% has a significant positive slope. If we carried this out further than 5 days we can assume it would achieve a similar slope to the other categories.

Why the swift partial recovery for 10-20%? One point to note is that of all the stocks found in this category their average drop on that initial day was about 12%. We then see them reach an average daily price high of about 9.5%

rare for a stocks highest trade price to never reach it's close on the previous day, especially during a generally bullish market.

The stark contrast between the 10-20% bucket vs. the others is very surprising. All other categories have a negatively-sloped line but 10-20% has a significant positive slope. If we carried this out further than 5 days we can assume it would achieve a similar slope to the other categories.

Why the swift partial recovery for 10-20%? One point to note is that of all the stocks found in this category their average drop on that initial day was about 12%. We then see them reach an average daily price high of about 9.5% higher than the close on the day of the drop, so that's about an 80% recovery. One explanation is that often after a large downwards price shock the "value investors" will come in and start buying at the lower price.

Now, it's definitely debatable whether analyzing the daily price highs is representative of the true recovery of a stock, so we'll look at the daily closes next. The highs may be more applicable to active traders, rather than investors.

Tracking price close after the drop

Here are the average price closes by each bucket 1, 2, 3, 4 and 5 days after the initial drop compared to the close on the drop day:

• All stocks: 0.2%, -0.2%, -0.5%, 0.0%, 0.1%
• 1-5% drop: 0.15%, -0.1%, -0.5%, -0.15%, 0.0%
• 5-10% drop: 0.1%, -0.5%, -0.9%, -0.7%, -0.7%
• 10-20% drop: -0.4%, -0.7%, 2.6%, 2.5%, 5.9%

Analysis

The only surprise here is that the 5-10% group dropped more than the 1-5% group. This is a bit counter-intuitive since naturally the 5-10% group has more room for recovery. However, it's definitely feasible that the reasons for the price drops in the different categories would be different. This would obviously affect how willing investors are to pick up the stock after the drop.

Conclusion

The apparently significant ability for a stocks price to recover after a large downward price shock could be a useful addition to the selection process. Keep it in mind when a strong stock takes a bit hit as the market may be emotionally over-reacting to bad news.

Since the price highs, rather than closes, rebounded much more for the 5-10% and 10-20% drop buckets, compared to all stocks, active investors or traders would probably be more likely to take advantage than the average person.